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Multimedia Information Retrieval Using Fuzzy Cluster-Based Model Learning
Date
2017-07-12
Author
Sattari, Saeid
Yazıcı, Adnan
Metadata
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Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
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Multimedia data, particularly digital videos, which contain various modalities (visual, audio, and text) are complex and time consuming to model, process, and retrieve. Therefore, efficient methods are required for retrieval of such complex data. In this paper, we propose a multimodal query level fusion approach using a fuzzy cluster-based learning method to improve the retrieval performance of multimedia data. Experimental results on a real dataset demonstrate that employing fuzzy clustering achieves notable improvement in the concept-based query retrieval performance.
Subject Keywords
Correlation
,
Visualization
,
Multimedia communication
,
Videos
,
Correlation coefficient
,
Computational modeling
,
Semantics
URI
https://hdl.handle.net/11511/52897
Collections
Department of Computer Engineering, Conference / Seminar
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S. Sattari and A. Yazıcı, “Multimedia Information Retrieval Using Fuzzy Cluster-Based Model Learning,” Naples, Italy, 2017, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/52897.